JIANG Peng, male, born in 2001 in Yancheng, Jiangsu Province, Master's student in Golden Mantis School of Architecture, Soochow University, research area: landscape planning and design (Suzhou 215123)
XIAO Xiangdong, male, born in 1976 in Changde, Hunan Province, Ph.D., Professor, Doctoral Supervisor, and Head of Department of Landscape Architecture, Golden Mantis School of Architecture, Soochow University, research area: landscape planning and design, landscape architecture design (Suzhou 215123)
TAN Li, male, born in 1992 in Jianshi, Hubei Province, Ph.D., Associate Professor and Master's Supervisor at Golden Mantis School of Architecture, Soochow University, research areas: urban-rural green space networks, local landscape (Suzhou 215123)
Under the global aspiration for carbon neutrality, enhancing urban carbon sink capacity has become an increasingly critical focus for nations worldwide. As urbanization continues at an unprecedented pace globally, the rapid expansion of cities has led to notable changes in land use patterns and increased habitat fragmentation, thereby exerting profound impacts on regional carbon balances. The development and optimization of ecological networks have emerged as vital strategies for safeguarding ecological security and promoting sustainable development. In recent years, an expanding body of research has demonstrated that ecological network construction is closely linked to the enhancement of urban ecosystems' carbon sequestration capacities, confirming that it is an effective approach to achieving the overarching goal of global carbon neutrality. The cities within the Yangtze River Delta (YRD), a prominent emblem of China's modernization, exemplify typical conflicts between urban expansion and ecological preservation. These conflicts highlight the urgency of adopting integrated ecological planning to reconcile urban growth with ecological integrity. In this context, the present study selects Suzhou, a key city in the YRD, as a case to investigate ecological network construction and optimization. Employing the mainstream "ecological source areas-ecological resistance surface-ecological corridors" framework, the research identifies critical ecological sources through morphological spatial pattern analysis and landscape connectivity indices. 8 factors - including dem, slope, NDVI, population density, land use, land cover, and so on - are incorporated to comprehensively evaluate landscape resistance. Using a least-cost path model, a combined ecological resistance surface is developed to quantify landscape resistance. Building upon this, core ecological corridors are extracted utilizing circuit theory and gravity models, enabling the identification of key pathways for ecological flow and connectivity. These corridors form the backbone of Suzhou's ecological network system, designed to enhance habitat connectivity and ecological stability. Subsequently, complex network theory is introduced to model the ecological topological network of Suzhou, facilitating an analysis of its structural features and their relationship with carbon sequestration capacity. Metrics such as degree centrality, clustering coefficient, and eigenvector centrality are employed to examine the network's topological roles and their influence on ecological function. The analysis reveals that Suzhou's ecological network exhibits typical water-network spatial characteristics, with primary source habitats mainly comprising lakes and forests. Ecological corridors are predominantly aligned along urban rivers and tributaries, yet the spatial distribution of ecological resources displays a notable imbalance. Correlation analyses demonstrate that the carbon sequestration capacity of ecological sources is significantly positively related to network characteristics such as degree, clustering coefficient, and eigenvector centrality. Improving these metrics - by adding ecological "stepping stones" and expanding corridors - proves effective in enhancing the network's overall carbon sequestration function. Based on the above findings, the study proposes a series of ecological network optimization strategies aimed at ecological function restoration and carbon sequestration capacity enhancement. Notably, 11 ecological stepping stones and 15 new corridors are incorporated into the network. Robustness assessments - evaluating the network's resilience and attack tolerance - show that the optimized network demonstrates higher stability and resistance against disturbances, confirming the scientific validity and practical feasibility of the optimization approach. These results validate that targeted ecological network modifications can enhance its resilience and carbon sequestration capacity. The study's outcome highlights that Suzhou's ecological network embodies a water-centric spatial pattern, with key ecological sources mainly being lakes and forests, and corridors predominantly along rivers. Although the spatial distribution of ecological resources remains uneven, targeted interventions through adding stepping stones and corridors can significantly enhance the network's carbon sequestration ability. The research aims to deepen understanding of the spatial relationship between ecological topological structures and carbon sequestration capacity, providing a scientific foundation for ecological network optimization centered on ecological function recovery and carbon storage enhancement. Overall, this study offers valuable insights for optimizing urban ecological networks in water-rich cities, with significant implications for regional ecological resilience, biodiversity conservation, and carbon sink functions. The findings hold important theoretical and practical significance for advancing urban ecological planning and contributing to the broader goals of ecological security and climate change mitigation.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |